AIMC Topic: Emergency Medicine
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Daring to be wise: We are black boxes, and artificial intelligence will be the solution.
Emergency medicine Australasia : EMA
Jul 28, 2019
Emergency physicians seek wisdom through personal resilience, deliberate reasoning, clinical consensus and reflective practice. However, there is a limit to how useful psychological training, clinical guidelines and audit initiatives can be in the fa...
The Extended Supervised Learning Event (ESLE): Assessing Nontechnical Skills in Emergency Medicine Trainees in the Workplace.
Annals of emergency medicine
Jul 17, 2019
STUDY OBJECTIVE: The contribution of emergency medicine clinicians' nontechnical skills in providing safe, high-quality care in the emergency department (ED) is well known. In 2015, the UK Royal College of Emergency Medicine introduced explicit valid...
Machine Learning in Relation to Emergency Medicine Clinical and Operational Scenarios: An Overview.
The western journal of emergency medicine
Feb 14, 2019
Health informatics is a vital technology that holds great promise in the healthcare setting. We describe two prominent health informatics tools relevant to emergency care, as well as the historical background and the current state of informatics. We ...
A Review of Natural Language Processing in Medical Education.
The western journal of emergency medicine
Dec 12, 2018
Natural language processing (NLP) aims to program machines to interpret human language as humans do. It could quantify aspects of medical education that were previously amenable only to qualitative methods. The application of NLP to medical education...
Deep neural network improves fracture detection by clinicians.
Proceedings of the National Academy of Sciences of the United States of America
Oct 22, 2018
Suspected fractures are among the most common reasons for patients to visit emergency departments (EDs), and X-ray imaging is the primary diagnostic tool used by clinicians to assess patients for fractures. Missing a fracture in a radiograph often ha...
Validation of deep-learning-based triage and acuity score using a large national dataset.
PloS one
Oct 15, 2018
AIM: Triage is important in identifying high-risk patients amongst many less urgent patients as emergency department (ED) overcrowding has become a national crisis recently. This study aims to validate that a Deep-learning-based Triage and Acuity Sco...
Artificial intelligence and machine learning in emergency medicine.
Emergency medicine Australasia : EMA
Jul 16, 2018
Interest in artificial intelligence (AI) research has grown rapidly over the past few years, in part thanks to the numerous successes of modern machine learning techniques such as deep learning, the availability of large datasets and improvements in ...
How artificial intelligence could transform emergency department operations.
The American journal of emergency medicine
Jan 4, 2018
Identification of Long Bone Fractures in Radiology Reports Using Natural Language Processing to support Healthcare Quality Improvement.
Applied clinical informatics
Nov 9, 2016
BACKGROUND: Important information to support healthcare quality improvement is often recorded in free text documents such as radiology reports. Natural language processing (NLP) methods may help extract this information, but these methods have rarely...
A Novel Artificial Intelligence System for Endotracheal Intubation.
Prehospital emergency care
Mar 17, 2016
OBJECTIVE: Adequate visualization of the glottic opening is a key factor to successful endotracheal intubation (ETI); however, few objective tools exist to help guide providers' ETI attempts toward the glottic opening in real-time. Machine learning/a...
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